Here is the whole week on one page. You are looking at three years of Summit Gear monthly revenue. The last six months are held out — hidden. Every forecasting method on the menu is going to forecast those same six months, and we will score each one by how far it missed. But your gut goes first. You commit a forecast blind, then you watch eight methods, plain to fancy, try to beat it. Then you hedge the number you would actually ship. The lesson is not which model wins. It is that a more complex method is not automatically more accurate, and that a point estimate shipped without a range hides how far it can miss.
The shaded band on the right is the held-out window: the last six months (Jul–Dec 2025). The methods only ever saw the 30 months to its left. Click a legend chip to hide or show a line.
A SWAG is a scientific wild guess: the first number you put down before anyone runs a model. It is the baseline every method has to beat. Look at the shape of the 30 months you can see, and forecast the six you cannot. One number is enough to start: your best guess for a typical month in the held-out window. If you want to draw the path, open the per-month box.
Optional. Fill all six to forecast a shape (for example, a summer peak fading into winter). If any are blank, we use your single number above, held flat.
First we reveal the six months that were held out — the actuals, the truth every method is judged against. Then the methods land one at a time, plainest first. Each drops its forecast line on the chart above and posts its MAE (mean absolute error, the average miss in dollars) and RMSE (root mean squared error, the same miss but with the big misses weighted heavier). Watch the order they arrive in against the order they finish in.
Every method that has revealed, plus your SWAG, ranked by RMSE (lower is a smaller miss). Your row is highlighted. Watch where your gut lands as the better methods arrive.
| # | Method | MAE ($) | RMSE ($) |
|---|---|---|---|
| Lock in a SWAG and start revealing to build the board. | |||
Three methods have a knob. Turn it and its forecast recomputes and the board reorders live. Two things to notice: the tuned method rarely leaps to the top, and the moment you move a knob off its default the number becomes a what-if — an exploration, not the canonical backtest. Snap the knob back to the marked default to restore the scored number.
A point estimate with no range hides how far it can miss. The question is how you build the range. There are two realities. In the first, you reason the pad from evidence: the backtest error you just measured is the buffer the evidence supports, because it is literally how far this method has missed before. In the second, the boss says move it y% — up for a stretch target, down to sandbag. Sometimes that is real conservatism; often it is a number moved with no evidence behind it, and either way it has to be documented and flagged.
The winning method (SARIMAX) forecasts the next quarter, and the hedge band is its backtest MAE of — the evidence-based buffer, applied to the number that leaves the building. This is the forecast a controller can defend: a method, a measured error, and a measured range.